Anopheles mosquitoes are responsible for the transmission of malaria parasites of the genus Plasmodium. During its journey in the mosquito the parasite suffers severe losses in numbers due to immune defence mechanisms of the vector. The genome of A. Gambia, the major African vector, has been recently sequenced and is certain to accelerate studies on mosquito innate immunity and vector-parasite interactions. In this context a first pass genomic analysis identified, among others, 7 genes families coding for pattern recognition receptors (PRR), defined as proteins that recognize pathogen associated molecular patterns. One such family encodes the C-type lections (Cols) genes as carbohydrate recognition PRR. The CTL gene family in A. Gambia includes 22 members. A preliminary functional analysis of 10 members by Ran knockout in adult susceptible mosquitoes allowed the identification of two genes, CTLMA2 and CTL4, whose individual knockout in a susceptible mosquito strain induces complete penalization of P.berghei (rodent parasite) kookiness, hence, completely blocking parasite transmission. This striking phenotype suggests that these molecules are beneficial for parasite survival and development and, hence, constitute potential targets for blocking Plasmodium transmission in Anopheles. In this proposal we aim to study the role of CTLMA2 and CTL4 in Anopheles immunity. This involves assessing their expression profile in mosquitoes challenged with microbes and Plasmodium, and determining their mode of action by investigating potential interactions with the surface of Plasmodium kookiness, possible associations with other immunity-related proteins and their sugar specificity. Additionally, the remaining CTL genes will be functionally screened by Ran knockout and those showing interesting phenotypes will be subjected to a similar analysis. Results obtained from this study are expected to highlight the role of Cols in Anopheles innate immunity.
Fields of science
- medical and health scienceshealth sciencespublic and environmental healthepidemics preventionimmunisation
- natural sciencesbiological sciencesbiochemistrybiomoleculesproteins
- natural sciencescomputer and information sciencesartificial intelligencepattern recognition
- medical and health scienceshealth sciencesinfectious diseasemalaria
Call for proposal
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